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Reliable monitoring for the early fault diagnosis of gearbox faults is of great concern for the wind industry. This paper presents a novel approach for health condition monitoring (CM) and fault diagnosis in wind turbine gearboxes using vibration analysis. This methodology is based on a machine learning algorithm that generates a baseline for the identification of deviations from the normal operation conditions of the turbine and the intrinsic characteristic-scale decomposition (ICD) method for fault type recognition. Outliers picked up during the baseline stage are decomposed by the ICD method to obtain the product components which reveal the fault information. The new methodology proposed for gear and bearing defect identification was validated by laboratory and field trials, comparing well with the methods reviewed in the literature. [ABSTRACT FROM AUTHOR]

It is well-known that when a single-degree-of-freedom (sdof) system is excited by a continuous motion of the foundation, the force transmissibility, relating the force transmitted to the foundation to the applied force, equals the displacement transmissibility. Recent developments in the generalization of the transmissibility to multiple-degree-of-freedom (mdof) systems have shown that similar simple and direct relations between both types of transmissibility do not appear naturally from the definitions, as happens in the sdof case. In this paper, the authors present their studies on the conditions under which it is possible to establish a relation between force transmissibility and displacement transmissibility for mdof systems. As far as the authors are aware, such a relation is not currently found in the literature, which is justified by being based on recent developments in the transmissibility concept for mdof systems. Indeed, it does not appear naturally, but the authors observed that the needed link is present when the displacement transmissibility is obtained between the same coordinates where the applied and reaction forces are considered in the force transmissibility case; this implies that the boundary conditions are not exactly the same and instead follow some rules. This work presents a formal derivation of the explicit relation between the force and displacement transmissibilities for mdof systems, and discusses its potential and limitations. The authors show that it is possible to obtain the displacement transmissibility from measured forces, and the force transmissibility from measured displacements, opening new perspectives, for example, in the identification of applied or transmitted forces. With this novel relation, it becomes possible, for example, to estimate the force transmissibility matrix with the structure off its supports, in free boundary conditions, and without measuring the forces. As far as force identification is concerned, this novel approach significantly decreases the computational effort when compared to conventional approaches, as it requires only local information of the sets of coordinates involved. Numerical simulations and experimental examples are presented and discussed, to illustrate the proposed developments. [ABSTRACT FROM AUTHOR]

This paper proposes the reconstruction of forces, based on the direct and inverse problems of transmissibility in multiple degree of freedom (MDOF) systems. The objective and novelty are to use the force transmissibility to calculate reactions given the applied loads (and vice versa). This method, relating two sets of forces, proves to be an alternative to the common inverse problem based on the measurement of FRFs and operational accelerations to determine operational forces, as it can be advantageous in some cases. This implies the a priori knowledge of the transmissibility of the structure, either experimentally or numerically. In this study a finite element model is built, describing with enough accuracy the dynamic behavior of the structure. The numerical model will play a key role in the construction of the transmissibility matrix; this will be used to evaluate either the reaction or the applied forces, using experimental data. This constitutes a hybrid methodology, which is validated experimentally. The authors present several comparisons between reconstructed and experimentally measured sets of forces. It is shown that the proposed method is able to produce good results in the reconstruction of the forces, underlining its potential for other structures and possible applications. [ABSTRACT FROM AUTHOR]

One of the main objectives of Acoustic Emission (AE) monitoring is to identify approaching critical stage of damage in the structure before it fails. State-of-the-art AE analysis is done on the features in both the time and frequency domains. Many features such as centroid frequency, duration, rise-time, count and energy are dependent on acquisition settings; threshold and timing parameters. Incorrect acquisition settings may result in inaccurate classification of the AE source. This work proposes a new feature in the time domain signal based on 2nd order Renyi’s entropy, which proves to be efficient in identifying different stages of damage. Renyi’s entropy is a measure of uncertainty or randomness of the signals and is directly derived from the distribution of signal amplitude. Therefore, it is independent of threshold and timing parameters. The validity of the proposed parameter is investigated by performing AE monitoring during fatigue endurance test of 316L stainless steel. Digital Image Correlation (DIC) and global strain monitoring was carried out to relate material damage with AE activity. The result shows Renyi’s entropy to be an effective measure to identify critical stages of damage in the material.